1. Field of the Invention
The present invention relates generally to controlling traffic overload in a telecommunications network and, more particularly, to forecasting a response time of a media gateway for an overload control system of a telecommunications network.
2. Related Information
In telecommunications it is desired to transfer data through a wide bandwidth network, and as rapidly as possible. However, this must be balanced against the resources of the particular telecommunications network. Without proper control of the network resources, routing devices would soon become overloaded with data traffic and the telecommunications network would be out of service.
It is desirable, therefore, to forecast the overload of network resources in order to optimize the amount of traffic flow that a telecommunications network is capable of handling. Typically, the overload situation occurs at the bottlenecks of the telecommunications system where traffic is switched from one element to another or between networks. One such bottleneck occurs at a media gateway, where telecommunications data is converted from the format required for one type of network to the format required for another.
A common method to predict, or otherwise avoid, an overload situation in such a device is to predict a response time of the device and control the data flow to the device in accordance with the predicted response time. However, an accurate method and/or apparatus that efficiently and effectively forecasts the response time of a telecommunication device has, thus far, been elusive. One of the neglected problem aspects is alternative approaches to the principles of forecasting.
In one forecasting solution, it has been suggested to employ a moving averages technique, for example, to observe the mean average of response times for a period in the past. By observing past response times and averaging them over a number of observations, one could yield some kind of prediction about what the next future response time could be.
However, the problem with moving averages is that such a technique considers each observation equally. That is, a moving average gives no credence to the recentness of events. This is not compatible in telecommunications devices, such as the media gateway mentioned, where recent data may be more relevant. Such systems tend to be event driven and recent events have a tendency to be more relevant.
In addition, a moving average requires analysis of a large number of parameters. When the observation averaging period is relatively long, the number of parameters (and subsequent calculations) becomes unwieldy. This shortcoming is especially acute in telecommunications systems where the speed of transferring data takes precedence over computations. In telecommunications, even a small number of analyzed parameters can unsatisfactorily overland a device.
A somewhat better solution to forecasting is provided by a time-series exponential forecast. With this technique, exponentially less weight is given to older data such that a prediction of a future event is based on more heavily weighted recent data. Thus, the degree to which recent events and data are considered increases exponentially. Given a satisfactory time-series forecast technique, such a forecast could be fine-tuned for telecommunications solutions which are event driven.
The known time-series forecast, however, suffers from a number of disadvantages, making such forecasting unappealing for telecommunications applications. What has been misunderstood with the use of this forecasting technique in telecommunications are the fundamental principles underlying this technique. These principles will be discussed in more detail in relation to the present invention. Further, it is not necessary to review the afore-mentioned forecasting techniques as a general understanding therefor can be attained from the published works of Brown, R. G., Smoothing, Forecasting And Prediction Of Discrete Time Series, Prentice-Hall, Inc., Englewood Cliffs, N.J., 1963, the contents of which are incorporated herein in their entirety.
Another deficiency in present telecommunication systems is the lack of forecasting specifically addressing the particular problems that arise in such telecommunications devices as the media gateway. As mentioned, the operation of such devices are event driven, and often a relatively long time elapses between events. In attempting to forecast an overload situation, a lapse of even a few seconds between events is problematic. In particular, the system shuts down a device when a forecast predicts an overload. To restart the device, the operator typically notices the failure a few seconds after system overload, and restarts the system. However, the remnant forecast that reflected the overload condition is still resident in the system. Thus, even though the device may no longer be overloaded, the system acts on a ‘false’ overload condition and rejects further call traffic.
This situation is prohibitive to testing in a laboratory environment. In such an environment, overload traffic is offered to the system and the traffic is suddenly stopped. When the traffic is restarted, the system has had time to settle and the traffic restarts below the overloaded level. However, due to the above-described problem the overload control remains in effect for a few event sequences and rejects any attempts to restart the device. As a result, the lab technician is impeded from continuing testing of the network. In telecommunications laboratories, where testing of new concepts is important for product development, such shortcomings must be resolved. In the real world, the impact of such problems could cause a system to lock up, resulting in a network catastrophe and a likely loss of subscribers.
It should also not be underestimated that even moderate forecasting computations are unwieldy in a telecommunications environment. Telecommunication devices require fast switching of traffic and any extraneous computations, however simple, degrade system performance. With reference to a Unix™ environment, for example, it has been found during the development of the present invention that floating point computations yield poor performance results. Furthermore, the use of numerous parameters in these forecasting calculations not only requires additional memory, it geometrically complicates the forecasting computation.
The aforementioned problems will become starkly apparent when contrasted with the features and advantages described in the detailed description.